Simulating Organogenesis in COMSOL: Comparison Of Methods For Simulating Branching Morphogenesis

During organogenesis tissue grows and deforms. The growth processes are controlled by diffusible proteins, so-called morphogens. Many different patterning mechanisms have been proposed. The stereotypic branching program during lung development can be recapitulated by a receptor-ligand based Turing model. Our group has previously used the Arbitrary Lagrangian-Eulerian (ALE) framework for solving the receptor-ligand Turing model on growing lung domains. However, complex mesh deformations which occur during lung growth severely limit the number of branch generations that can be simulated. A new Phase-Field implementation avoids mesh deformations by considering the surface of the modelling domains as interfaces between phases, and by coupling the reaction-diffusion framework to these surfaces. In this paper, we present a rigorous comparison between the Phase-Field approach and the ALE-based simulation

Using open ended, ill formed problems to develop and assess Engineering Mathematics competencies.

The purpose of this paper is to report upon how an engineering mathematics class was used to provide a vehicle for students to develop mathematical competencies and hence higher order thinking skills within the broader field of engineering education. Specifically it provided students with the opportunities to think mathematically, reason mathematically, pose and resolve mathematical problems, to use technology to model resolutions, interpret and handle mathematical symbolism and to communicate their resolutions to peers and staff. Using the report produced by the Mathematics Working Group of SEFI (European Society for Engineering Education), which details a framework for mathematics curricula in engineering education (SEFI, 2013), a methodology was identified. This methodology was also based on work previously undertaken by the author (Peters, 2017; Peters, 2015). In section 2.1 (p 13) the report lists and describes a set of eight mathematical competencies: (1) Thinking mathematically, (2) reasoning mathematically, (3) posing and solving mathematical problems, (4) modelling mathematically, (5) representing mathematical entities, (6) handling mathematical symbols and formalism, (7) communicating in, with, and about mathematics and, (8) making use of aids and tools. The report also points out the importance of developing assessment procedures pertinent to competency acquisition (p7). The evidence from this investigation concludes that the majority of students found the experience challenging but worthwhile. They considered they had learnt important skills including the ability to form assumptions, persistence, time management, project management and an enhancement of their mathematical skills in relation to engineering

The second order perturbation approach for elliptic partial differential equations on random domains

The present article is dedicated to the solution of elliptic boundary value problems on random domains. We apply a high-precision second order shape Taylor expansion to quantify the impact of the random perturbation on the solution. Thus, we obtain a representation of the solution with third order accuracy in the size of the perturbation's amplitude. The major advantage of this approach is that we end up with purely deterministic equations for the solution's moments. In particular, we derive representations for the first four moments, i.e., expectation, variance, skewness and kurtosis. These moments are efficiently computable by means of boundary integral equations. Numerical results are presented to validate the presented approach

Enhanced Ammonia Oxidation Catalysis by a Low-Spin Iron Complex Featuring Cis Coordination Sites

The goal of using ammonia as a solar fuel motivates the development of selective ammonia oxidation (AO) catalysts for fuel cell applications. Herein, we describe Fe-mediated AO electrocatalysis with [(bpyPy₂Me)Fe(MeCN)₂]²⁺, exhibiting the highest turnover number (TON) reported to date for a molecular system. To improve on our recent report of a related iron AO electrocatalyst, [(TPA)Fe(MeCN)₂]²⁺ (TON of 16), the present [(bpyPy₂Me)Fe(MeCN)₂]²⁺ system (TON of 149) features a stronger-field, more rigid auxiliary ligand that maintains cis-labile sites and a dominant low-spin population at the Fe(II) state. The latter is posited to mitigate demetalation and hence catalyst degradation by the presence of a large excess of ammonia under the catalytic conditions. Additionally, the [(bpyPy₂Me)Fe(MeCN)₂]²⁺ system exhibits a substantially faster AO rate (ca. 50×) at significantly lower (∼250 mV) applied bias compared to [(TPA)Fe(MeCN)₂]²⁺. Electrochemical data are consistent with an initial E₁ net H-atom abstraction step that furnishes the cis amide/ammine complex [(bpyPy₂Me)Fe(NH₂)(NH₃)]²⁺, followed by the onset of catalysis at E₂. Theoretical calculations suggest the possibility of N–N bond formation via multiple thermodynamically plausible pathways, including both reductive elimination and ammonia nucleophilic attack. In sum, this study underscores that Fe, an earth-abundant metal, is a promising metal for further development in metal-mediated AO catalysis by molecular systems

Comparing and improving hybrid deep learning algorithms for identifying and locating primary vertices

Using deep neural networks to identify and locate proton-proton collision points, or primary vertices, in LHCb has been studied for several years. Preliminary results demonstrated the ability for a hybrid deep learning algorithm to achieve similar or better physics performances compared to standard heuristic approaches. The previously studied architectures relied directly on hand-calculated Kernel Density Estimators (KDEs) as input features. Calculating these KDEs was slow, making use of the DNN inference engines in the experiment's real-time analysis (trigger) system problematic. Here we present recent results from a high-performance hybrid deep learning algorithm that uses track parameters as input features rather than KDEs, opening the path to deployment in the real-time trigger system.Comment: Proceedings for the ACAT 2022 conferenc

Evaluating Title VII Exposure in a Manufacturing Setting: A Case Study for Human Resource Management Students

Since Title VII of the Civil Rights Act of 1964 became an established part of the employment legal framework, human resource management professionals and compliance officers have played a vital role in evaluating their companies’ vulnerability to litigation based on perceived violations of Title VII, the Age Discrimination in Employment Act, the American with Disabilities Act, and other associated equality protection legislation. Factors to be considered include the plaintiff’s burden of proof, legitimate business defenses, and collection and evaluation of reliable data. This case study calls upon human resource management graduate students to evaluate the potential exposure of a defense manufacturer to gender discrimination litigation, and has been presented in an online learning environment

Influence of Slip on the Plateau-Rayleigh Instability on a Fibre

The Plateau-Rayleigh instability of a liquid column underlies a variety of fascinating phenomena that can be observed in everyday life. In contrast to the case of a free liquid cylinder, describing the evolution of a liquid layer on a solid fibre requires consideration of the solid-liquid interface. In this article, we revisit the Plateau-Rayleigh Instability of a liquid coating a fibre by varying the hydrodynamic boundary condition at the fibre-liquid interface, from no-slip to slip. While the wavelength is not sensitive to the solid-liquid interface, we find that the growth rate of the undulations strongly depends on the hydrodynamic boundary condition. The experiments are in excellent agreement with a new thin film theory incorporating slip, thus providing an original, quantitative and robust tool to measure slip lengths

Designing and implementing effective campus sustainability in Saudi Arabian universities: an assessment of drivers and barriers in a rational choice theoretical context

Saudi Arabia is a developing country that is experiencing a rapid growth in its population and level of urbanisation. Higher education (HE) in the country has developed rapidly over the last ten years, and it is still moving through numerous major reforms. Largely, the concept of sustainability has not yet been formally adopted in public institutions in a way that could sufficiently remedy the range of activities that currently impact negatively on the environment. The central aim of this paper is to examine the extent to which planning and action for sustainability is currently being taken on university campuses in Saudi Arabia, and to review the opportunities and challenges for encouraging and enabling further progress to this end. The research that the paper draws on specifically investigated the influence of decision makers’ personal knowledge and perceptions within Facilities and Project Management (FPM) departments at selected Saudi universities, and the constraints faced by FPM decision makers with regard to the promotion of sustainability on campus. This exploration was supported by the development of a theoretical framework that draws on rational choice theory (RCT). The research revealed mixed levels of prevailing knowledge and awareness towards sustainability among FPM decision makers within the case study university campuses. Cost notably came across as a dominant influence on FPM decision makers’ choices and decisions, and it undoubtedly plays an important role in shaping the decision-making process alongside other key organisational factors. A number of barriers facing the incorporation of sustainability emerged with clarity, such as the lack of supportive leadership, the lack of sustainability knowledge and awareness among senior management and an absence of sustainability-related legislation policy or strategic direction in the HEIs concerned